On-line adaptive observer for buildings based on wave propagation approach

2017 ◽  
Vol 24 (16) ◽  
pp. 3758-3778 ◽  
Author(s):  
Jesús Morales-Valdez ◽  
Luis Alvarez-Icaza ◽  
Antonio Concha
Keyword(s):  
Wave Propagation ◽  
Least Squares Method ◽  
Health Assessment ◽  
Observer Design ◽  
Adaptive Observer ◽  
Recursive Least Squares ◽  
Beam Model ◽  
Line System ◽  
Shear Beam ◽  
On Line

A novel on-line system identification method for shear beam building models, based on a wave propagation approach, is developed as an alternative solution to modal analysis methods for the health assessment of multi-story buildings. A discrete shear beam model is introduced that is used to design an adaptive observer, allowing for the estimation of displacements and velocities, as well as the unknown shear wave velocities and damping coefficients in real-time. The adaptive observer design is based only on acceleration measurements, does not need a coordinate transformation, and uses the normalized recursive least squares method with forgetting factor and a parameter projection scheme to achieve stronger convergence. Moreover, the proposed identification scheme employs a novel parameterization based on linear integral filters, which eliminates constant disturbances and attenuates measurement noise. The algorithm efficiency is demonstrated through experimental results on a reduced scale five-story building.

Wave propagation in a doubly tapered shear beam: Model and application to a pyramid‐shaped skyscraper

2021 ◽  
Author(s):  
Maria I. Todorovska ◽  
Eyerusalem A. Girmay ◽  
Fangbo Wang ◽  
Mohammadtaghi Rahmani
Keyword(s):  
Wave Propagation ◽  
Beam Model ◽  
Shear Beam ◽  
Shear Beam Model

On-Line Flank Wear Estimation Using an Adaptive Observer and Computer Vision, Part 1: Theory

1993 ◽  
Vol 115 (1) ◽  
pp. 30-36 ◽  
Author(s):  
Jong-Jin Park ◽  
A. Galip Ulsoy
Keyword(s):  
Computer Vision ◽  
Cutting Force ◽  
Flank Wear ◽  
Adaptive Observer ◽  
Cutting Conditions ◽  
Recursive Least Squares ◽  
Integrated Method ◽  
On Line ◽  
Vision Technique ◽  
Computer Vision Technique

The problem of developing a reliable on-line flank wear measurement system is treated using the integration of an adaptive observer, based on cutting force measurement, and computer vision. In this part of the paper, the theoretical basis and design of the integrated method is presented. Implementation issues are discussed in Part 2 of the paper along with experimental results. The flank wear is modeled as the summation of two unmeasurable states in a nonlinear dynamic system realized in state space equation form. The inputs to the system are the feed, the cutting speed, and the depth of cut (i.e., the cutting conditions) and the output is the cutting force. Based on a simplified version of this flank wear model, an adaptive observer is designed by combining the observer technique and the recursive least squares parameter estimation algorithm. The designed adaptive observer indirectly measures the flank wear and simultaneously estimates one unknown model parameter, using measurements of the cutting force and the cutting conditions. The adaptive observer is integrated with a computer vision system which can directly measure the flank wear with good accuracy. In the integrated system, the adaptive observer is intermittently calibrated using direct flank wear measurements via computer vision. In this part of the paper, the integrated method is presented without referring to any specific computer vision technique. However, a computer vision technique is developed in Part 2 of the paper for an experimental evaluation of the proposed method. The fundamental idea behind the proposed integrated method is that a less accurate indirect flank wear measuring method (i.e., the adaptive observer) is intermittently calibrated by a more accurate direct measurement method (i.e., computer vision).

scholarly journals On-line monitoring of intrinsic PEEP in ventilator-dependent patients

2000 ◽  
Vol 89 (3) ◽  
pp. 985-995 ◽  
Author(s):  
G. Nucci ◽  
M. Mergoni ◽  
C. Bricchi ◽  
G. Polese ◽  
C. Cobelli ◽  
...  
Keyword(s):  
Least Squares Method ◽  
Recursive Least Squares ◽  
Intrinsic Peep ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Mechanically Ventilated ◽  
Mechanically Ventilated Patients ◽  
On Line ◽  
Highly Correlated ◽  
Ventilated Patients

Measurement of the intrinsic positive end-expiratory pressure (PEEPi) is important in planning the management of ventilated patients. Here, a new recursive least squares method for on-line monitoring of PEEPi is proposed for mechanically ventilated patients. The procedure is based on the first-order model of respiratory mechanics applied to experimental measurements obtained from eight ventilator-dependent patients ventilated with four different ventilatory modes. The model PEEPi (PEEPi,mod) was recursively constructed on an inspiration-by-inspiration basis. The results were compared with two well-established techniques to assess PEEPi: end-expiratory occlusion to measure static PEEPi (PEEPi,st) and change in airway pressure preceding the onset of inspiratory airflow to measure dynamic PEEPi (PEEPi,dyn). PEEPi,mod was significantly correlated with both PEEPi,dyn( r = 0.77) and PEEPi,st ( r= 0.90). PEEPi,mod (5.6 ± 3.4 cmH2O) was systematically >PEEPi,dyn and PEEPi,st(2.7 ± 1.9 and 8.1 ± 5.5 cmH2O, respectively), in all the models without external PEEP. Focusing on the five patients with chronic obstructive pulmonary disease, PEEPi,mod was significantly correlated with PEEPi,st ( r = 0.71), whereas PEEPi,dyn ( r = 0.22) was not. When PEEP was set 5 cmH2O above PEEPi,st, all the methods correctly estimated total PEEP, i.e., 11.8 ± 5.3, 12.5 ± 5.0, and 12.0 ± 4.7 cmH2O for PEEPi,mod, PEEPi,st, and PEEPi,dyn, respectively, and were highly correlated (0.97–0.99). We interpreted PEEPi,mod as the lower bound of PEEPi,st and concluded that our method is suitable for on-line monitoring of PEEPi in mechanically ventilated patients.

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